sandia national laboratories nisac’s core partners are sandia national laboratories and los alamos...
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SandiaNationalLaboratories
NISAC’s core partners are Sandia National Laboratories and Los Alamos National Laboratory. Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy under contract DE-AC04-94AL85000. Los Alamos National Laboratory
is operated by the University of California for the United States Department of Energy under contract W-7405 ENG-36.
Simulation and Analysis of Cascading Simulation and Analysis of Cascading Failure in Critical InfrastructureFailure in Critical Infrastructure
Robert Glass1, Walt Beyeler1, Kimmo Soramäki2, Morten Bech3 and Jeffrey Arnold3
1Sandia National Laboratories2European Central Bank
3Federal Reserve Bank of New York
SandiaNationalLaboratories
SandiaNationalLaboratories
log(Size)
log(
Fre
quen
cy)
“Big” events are notrare in many such systems
Earthquakes: Guthenburg-Richter
Wars, Epidemics, Cities
Power Blackouts Telecom outages“heavy tail”
region
Extinctions, Forest fires
Traffic jams, Stock crashes
First Stylized Fact: Multi-component Systems First Stylized Fact: Multi-component Systems often have power-laws & “heavy tails”often have power-laws & “heavy tails”
SandiaNationalLaboratories
SandiaNationalLaboratories
Dissipation
Temperature
Cor
rela
tion
Tc
External Drive
What keeps a non-equilibrium system at a phase boundary?
Equilibrium systems:
Power Law - Critical behavior – Phase transitionsPower Law - Critical behavior – Phase transitions
e.g., Magnets & the Curie point
SandiaNationalLaboratories
SandiaNationalLaboratories
Drive
1987 Bak, Tang, Wiesenfeld’s “Sand-pile” or 1987 Bak, Tang, Wiesenfeld’s “Sand-pile” or “Cascade” Model“Cascade” Model
Cascade fromLocal Rules
RelaxationLattice
“Self-Organized Criticality”power-laws
fractals in space and time
SandiaNationalLaboratories
SandiaNationalLaboratories
Illustrations of natural and constructed network systems from Strogatz [2001].
Food WebFood Web
New York state’sNew York state’sPower GridPower Grid
MolecularMolecularInteractionInteraction
Second Stylized Fact: Networks are UbiquitousSecond Stylized Fact: Networks are Ubiquitous
SandiaNationalLaboratories
SandiaNationalLaboratories
tolerant to random failure
Properties:vulnerable to
informed attack…
Hierarchical with “King-pin” nodes
Special properties of the “Scale-free” networkSpecial properties of the “Scale-free” network
Power-law degree distribution
SandiaNationalLaboratories
SandiaNationalLaboratories
NetworkNodesLinks
OtherNetworks
Drive
Dissipation
ActorsAdapt& Rewire
PolyNetBuilt in Repast
Tailored Interaction Rules
Our Conceptual Approach: Rules ON Networks Our Conceptual Approach: Rules ON Networks for Bottoms up Simulation of Infrastructuresfor Bottoms up Simulation of Infrastructures
SandiaNationalLaboratories
SandiaNationalLaboratories
Stylized Physical Infrastructure Applications:High Voltage Electric Power Grids
Payment and Banking Systems
Epidemics
Self-organized Terrorist/Extremist groups
Stylized Social Applications:
Social/Report Network Evolution
Where we are headed:Combined Physical-Human “Infrastructure” Systems
Information Networks
Crisis and recovery from WMD & Bio attacks
Physical + SCADA + Market + Policy Forcing
Development & ApplicationsDevelopment & Applications
Abstract Studies
SandiaNationalLaboratories
SandiaNationalLaboratories
BTW sand-pile on varied topologyBTW sand-pile on varied topology
Fish-netor Donut
Scale-free
BTW Sand-pile
0
20000
40000
60000
80000
100000
120000
1 59 117 175 233 291 349 407 465 523 581 639 697 755 813 871 929 987
time steps
Cas
cad
e S
ize
(no
des
)
Square Lattice "Fish-net" Scale-free
time
size
BTW Sand-pile
-6
-4
-2
0
2
4
6
0 1 2 3 4 5 6
log(size)lo
g(f
req
uen
cy)
Square Lattice "Fish-net" Scale-Free
Roll-off points Roll-off points
Linear (Scale-Free) Linear (Square Lattice "Fish-net")
log(size)log(
freq
)Random sinksSand-pile rules and drive10,000 nodes
SandiaNationalLaboratories
SandiaNationalLaboratories
Cascading BlackoutsCascading Blackouts
Fish-netor Donut
Scale-free
Sources, sinks, relay stations, 400 nodes
Power-Grid: Scale-Free
0
50
100
150
200
250
300
350
0 1000 2000 3000 4000 5000 6000 7000
time stepssi
ze (
no
des
)
timesi
ze
Scale-free
Power-Grid: Square Lattice "Fish-net"
0
50
100
150
200
250
300
350
400
450
0 50000 100000 150000 200000
time steps
size
(n
od
es)
time
size
Fish-net
DC circuit analogy, load, safety factorsRandom transactions between sources and sinks
SandiaNationalLaboratories
SandiaNationalLaboratories
Trading Day
0Openingbalance
adapts tocontrol risk
0
Pay
Training Period
Cascading PeriodB
alan
ce
Time
Bal
ance
0
Bal
ance
Time
Cascading Liquidity Loss within Payment SystemsCascading Liquidity Loss within Payment Systems
banks
payments
SandiaNationalLaboratories
SandiaNationalLaboratories
Cascading Liquidity in Scale-free NetworkCascading Liquidity in Scale-free Network
Fedwire
0
100
200
300
400
500
600
700
800
900
1000
0 100000 200000 300000 400000 500000 600000 700000 800000 900000 1000000
Time
Nu
mb
er o
f F
ailu
res
Realization 1, No Predictability Realization 1, 50% Predictability
Patterned Transactions
time
bank
de
faul
ts
Random removal vs Attack of the Highest Degree node
Fedwire
0
5000
10000
15000
20000
25000
30000
35000
0 200000 400000 600000 800000 1000000 1200000
Time
Ava
ilab
le L
iqu
idit
yRealization 6 Realization 7 Realization 4, Directed Realization 6, Directed
time
liqu
idit
y
SandiaNationalLaboratories
SandiaNationalLaboratories 13
Everyone
me
Nuclear Family
me
Classes (There are 6 of these)
me
Extended Family
me
Teen Extra
me
Cascading Infectious DiseasesCascading Infectious Diseases
KidsTeensAdultsSeniors
Agent classes
•Infectivity•Mortality•Immunity•Etc.
Class Specific Parameters
Teen Laura Glass’s Groups
Links&
Frequency
Parameters can change whenSymptomatic
SandiaNationalLaboratories
SandiaNationalLaboratories
0
500
1000
1500
2000
2500
3000
3500
0 50 100 150 200 250 300
time (days)
Nu
mb
er I
nfe
cted
0
500
1000
1500
2000
2500
3000
3500
0 50 100 150 200 250 300
time (days)
Nu
mb
er I
nfe
cted
0
500
1000
1500
2000
2500
3000
3500
0 50 100 150 200 250 300
time (days)
Nu
mb
er I
nfe
cted
0
500
1000
1500
2000
2500
3000
3500
0 50 100 150 200 250 300
time (days)
Nu
mb
er I
nfe
cted
14
Without Immunity
With Immunity & Mortality
Behavioral Changes when Symptomatic
Agent differentiation
Influenza Epidemic in Structured Village of 10,000:Influenza Epidemic in Structured Village of 10,000:Increasing RealismIncreasing Realism
Structure: Heterogeneous Network + Like with Like
SandiaNationalLaboratories
SandiaNationalLaboratories
Flu Epidemic Mitigation: Vaccination Strategies Flu Epidemic Mitigation: Vaccination Strategies
0
500
1000
1500
2000
2500
3000
0 20 40 60 80 100 120
time (days)
nu
mb
er
infe
cte
d
Kids & Teens!
Current policy
Seniors only (yellow)
<60% required
Network Structure + Physics of Transmission ProcessAllows Effective Mitigation Design
SandiaNationalLaboratories
SandiaNationalLaboratories
General Remarks:General Remarks:
Developmental directions
Generalization/Abstraction
Detailed applications withDomain experts
Concepts from Complexity Science are valuable and allow a simulation approach for critical infrastructures that is flexible and has wide
ranging applications
Focus on POLICY
Tools/Insight for Rapid deploymentEncapsulation/Integration-NABLE-BOF simulator
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